This open access book constitutes revised selected papers from the International Workshops held at the Third International Conference on Process Mining, ICPM 2021, which took place in Eindhoven, The Netherlands, during October 31–November 4, 2021. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-l…
This open access book systematically investigates the topic of entity alignment, which aims to detect equivalent entities that are located in different knowledge graphs. Entity alignment represents an essential step in enhancing the quality of knowledge graphs, and hence is of significance to downstream applications, e.g., question answering and recommender systems. Recent years have witnessed …
This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-train…
A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges.OCLC-licensed vendor bibliographic record.
This book constitutes the refereed proceedings of the 19th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2015, held in Warsaw, Poland, in April 2015. The 36 extended abstracts were carefully reviewed and selected from 170 submissions. They report on original research in all areas of computational molecular biology and bioinformatics.
"Explores the collection of children's biometric, educational, and social media data and its immediate and downstream effects for individuals and families"--OCLC-licensed vendor bibliographic record.
A concise introduction to fundamental methods for finding and extracting relevant information from the ever-increasing amounts of biomedical text available.
A guide to principles and methods for the management, archiving, sharing, and citing of linguistic research data, especially digital data.Doing language science depends on collecting, transcribing, annotating, analyzing, storing, and sharing linguistic research data. This volume offers a guide to linguistic data management, engaging with current trends toward the transformation of linguistics i…
In science, business, and policymaking—anywhere data are used in prediction—two sorts of problems requiring very different methods of analysis often arise. The first, problems of recognition and classification, concerns learning how to use some features of a system to accurately predict other features of that system. The second, problems of causal discovery, concerns learning how to predict…